A Seamless and Efficient Transition Algorithm For Aerial Drone Multicasting

Tu, Wanqing

Abstract

Drone communications make use of line-of-sight coverage of drones to realise services that ground devices may not support. Many relevant applications such as video capture by drones and drone traffic management, require group communications between drones to efficiently disseminate data. In this paper, we study high-performance yet resource-efficient multicasting between drones that may change their locations in order to fulfill their missions. This is achieved by proposing novel trajectories for mobile drones to seamlessly transit, with controlled travel distances and traffic overheads, in a multicasting environment. The presented efficient transition via trajectory adjustment (ETTA) algorithm is developed based on our analysis of the condition that determines when a straight-line trajectory between the origin and destination of a drone is not seamless. The algorithm then proposes the trajectory adjustment schemes that form a new interference-controlled and travel-distance-controlled trajectory to replace an interrupted straight-line trajectory. Our NS2 simulation results demonstrate that ETTA, as compared to other mobile multicasts, can achieve guaranteed performance in a multicast with heavier traffic loads.

Citation

Tu, W. (2021, December). A Seamless and Efficient Transition Algorithm For Aerial Drone Multicasting. Presented at 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC), Las Vegas, NV

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC)
• Online Publication Date: Mar 11, 2021
• Publication Date: 2021
• Deposit Date: Oct 27, 2021
• Publicly Available Date: Oct 27, 2021
• Pages: 1-6
• Series ISSN: 2331-9860
• Book Title: CCNC 2021: 2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC)
• DOI: https://doi.org/10.1109/ccnc49032.2021.9369559
• Public URL: https://durham-repository.worktribe.com/output/1138919
• Additional Information: Date of Conference: 09-12 January 2021